Issue 76, 2017

A fluorescence switching sensor based on graphene quantum dots decorated with Hg2+ and hydrolyzed thioacetamide for highly Ag+-sensitive and selective detection

Abstract

A selective fluorescent sensor based on graphene quantum dots (GQDs) was developed for the determination of silver ions (Ag+). The GQDs were prepared by the citric acid pyrolysis method. In the presence of mercury ions (Hg2+), the fluorescence intensity of the GQDs decreased linearly and it was fully recovered by the hydrolysis of thioacetamide (TAA), giving hydrogen sulfide in the reaction system. This research study was aimed at using the fluorescence turn-off sensor for the selective determination of Ag+. Upon the addition of Ag+, the fluorescence intensity of the generated sulfide-(Hg2+ quenched GQDs) decreased as a linear function of the Ag+ concentration. Then, the acquired GQDs showed steady, selective, and highly sensitive detection of Ag+. The experimental parameters affecting the fluorescence turn-on/off sensor were investigated and optimized. The optimum conditions included 4 μM Hg2+ concentration, 70 μM TAA concentration, solution pH of 7 and a 5 min reaction time. Under the optimized conditions, the working linear concentration range, limit of detection and limit of quantification for Ag+ were 0.5–10.0, 0.18 and 0.60 μM, respectively. The proposed method was successfully applied for the selective determination of trace amounts of Ag+ in five real water samples with satisfying levels of recovery (89.31–114.08%).

Graphical abstract: A fluorescence switching sensor based on graphene quantum dots decorated with Hg2+ and hydrolyzed thioacetamide for highly Ag+-sensitive and selective detection

Article information

Article type
Paper
Submitted
17 aug 2017
Accepted
02 okt 2017
First published
13 okt 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 48058-48067

A fluorescence switching sensor based on graphene quantum dots decorated with Hg2+ and hydrolyzed thioacetamide for highly Ag+-sensitive and selective detection

P. Kaewanan, P. Sricharoen, N. Limchoowong, T. Sripakdee, P. Nuengmatcha and S. Chanthai, RSC Adv., 2017, 7, 48058 DOI: 10.1039/C7RA09126E

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